def testKernelRegressionGram(self):
n, d = 100, 20
xs = self.rng.normal(size=(n, d))
kernel = lambda x, y: jnp.dot(x, y)
np.testing.assert_allclose(kernel_lsq.gram(kernel, xs),
jnp.dot(xs, xs.T),
atol=1E-5)
def testKernelRegressionGram(self):
n, d = 100, 20
rng = onp.random.RandomState(0)
truth = rng.randn(d)
xs = rng.randn(n, d)
ys = np.dot(xs, truth)
kernel = lambda x, y: np.dot(x, y)
assert np.all(kernel_lsq.gram(kernel, xs) == np.dot(xs, xs.T))
def testKernelRegressionGram(self):
n, d = 100, 20
rng = np.random.RandomState(0)
xs = rng.randn(n, d)
kernel = lambda x, y: jnp.dot(x, y)
self.assertAllClose(kernel_lsq.gram(kernel, xs),
jnp.dot(xs, xs.T),
check_dtypes=False)